penaltyLearning: Penalty Learning

Implementations of algorithms from Learning Sparse Penalties for Change-point Detection using Max Margin Interval Regression, by Hocking, Rigaill, Vert, Bach <> published in proceedings of ICML2013.

Version: 2024.1.25
Depends: R (≥ 2.10)
Imports: data.table (≥ 1.9.8), ggplot2
Suggests: neuroblastoma, jointseg, testthat, future, future.apply, directlabels (≥ 2017.03.31)
Published: 2024-02-01
DOI: 10.32614/CRAN.package.penaltyLearning
Author: Toby Dylan Hocking
Maintainer: Toby Dylan Hocking <toby.hocking at>
License: GPL-3
NeedsCompilation: yes
Materials: NEWS
CRAN checks: penaltyLearning results


Reference manual: penaltyLearning.pdf


Package source: penaltyLearning_2024.1.25.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release (arm64): penaltyLearning_2024.1.25.tgz, r-oldrel (arm64): penaltyLearning_2024.1.25.tgz, r-release (x86_64): penaltyLearning_2024.1.25.tgz, r-oldrel (x86_64): penaltyLearning_2024.1.25.tgz
Old sources: penaltyLearning archive

Reverse dependencies:

Reverse imports: PeakSegJoint, PeakSegOptimal
Reverse suggests: aum, binsegRcpp, PeakSegDP


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